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Online Naive Bayes/Evidence
Method evidence record

Online Naive Bayes

Online Naive Bayes is an incremental adaptation of the classical Naive Bayes classifier that updates its class-conditional statistics one observation (or one mini-batch) at a time, making it well suited to data streams, very large datasets that cannot be held in memory, and settings where the model must adapt continuously as new labeled examples arrive.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Online (Incremental) Naive Bayes Classifier
Taxonomic method record · ml-model / machine-learning
  • Domingos, P. & Hulten, G. (2000). Mining high-speed data streams. Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 71–80. ACM. · DOI 10.1145/347090.347107
  • Online machine learning. Wikipedia. · URL
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Related methods

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Taxonomic bucketLogistic regression (ML)machine-suggested · Relational suggestion, not evidence.Same method familyNaive Bayesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketOnline Decision Treemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketOnline Learningmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketOnline Logistic Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised Naive Bayesmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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